Pqs Prompt Quality Score

by OnChainAIIntel

2 stars

295 downloads

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About

The world's first named AI prompt quality score. Score any LLM prompt before it hits any model — returns grade (A-F), score out of 40, percentile, and dimension breakdown across 8 quality dimensions.

Details

Author: OnChainAIIntel
GitHub stars: 2
Downloads: 295
Categories: Other

- Scores prompts on 8 dimensions (clarity, specificity, etc.)
- Returns a 0–80 score and A–F grade
- Free score_prompt tool with per-IP rate limits
- Pro optimize_prompt rewrites and compares prompts
- Side-by-side before/after outputs from a frontier model
- Can be used as a pre-inference quality gate
- Supports self-hosting via PQS_BASE environment variable

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Pqs Prompt Quality Score

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

From the repository

Install via npx -y pqs-mcp-server in your Claude Desktop config (stdio) or use the remote HTTP URL https://promptqualityscore.com/api/mcp for streamable-HTTP clients. Run npx pqs-mcp-server directly. The free score_prompt tool requires no API key; the optimize_prompt tool requires a Pro subscription ($19.99/mo). Use the quality gate pattern to reject prompts scoring below 56/80.

`score_prompt`

Score a prompt's quality across 8 dimensions BEFORE sending it to an expensive model. Returns a 0-80 score, an A-F grade, the per-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. USE WHEN: - The user is workshopping a prompt and asks "is this good?" / "will this work?" / "should I add more detail?" - The user is about to send a long or expensive prompt to GPT-4, Claude Opus, or any frontier model, especially in a batch or automation context where rework is costly. - The user mentions iterating on a prompt that produced poor output and wants to diagnose what's missing. - The user pastes a prompt and asks for feedback on it. DO NOT USE WHEN: - The user is asking you to write a prompt for them (write it yourself first, then optionally call score_prompt to verify). - The prompt is conversational chat (this scores task-shaped prompts). COST: Free, no API key required. Rate-limited per IP: 5/min, 10/day, 100/month. If the user exceeds the limit, the response will include a structured upgrade path with subscribe and account URLs. LATENCY: ~2 seconds.

`optimize_prompt`

Rewrite a prompt to score higher on the PQS rubric, AND show before/after output comparisons so the user can see the impact. Returns the optimized prompt, the original PQS score, the optimized PQS score, and side-by-side sample outputs from a frontier model using both versions. USE WHEN: - The user got a low score from score_prompt and asks how to improve. - The user explicitly asks to "improve" / "rewrite" / "fix" / "optimize" a prompt they pasted. - The user is dissatisfied with output quality from a previous prompt and asks how to get better results. - score_prompt returned a suggestion to invoke this tool. DO NOT USE WHEN: - The user just asked for a score (use score_prompt only — don't double up). - The user wants you to write a new prompt from scratch (write it directly). REQUIRES: A PQS API key from a Pro subscription ($19.99/month, 1,000 calls/mo, includes batch + A/B comparison). If the user has not provided one, the tool returns a clear subscription URL — pass that response to the user verbatim. Do not invent or guess API keys. There is no free trial of this tool; the user must subscribe before the first call. COST: Counted against your Pro subscription's monthly call quota. LATENCY: ~6-8 seconds.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "pqs   prompt quality score": {
            "pqs": {
                "command": "npx",
                "args": [
                    "pqs-mcp-server"
                ]
            }
        }
    }
}

McpServers

{
    "pqs": {
        "command": "npx",
        "args": [
            "pqs-mcp-server"
        ]
    }
}

PQS MCP Server

Score prompt quality before it reaches any AI model. An MCP server for PQS.

Score and optimize LLM prompts before they hit any model. Built on PEEM, RAGAS, MT-Bench, G-Eval, and ROUGE.

Install

Claude Desktop (stdio)

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json):

{

  "mcpServers": {

    "pqs": {

      "command": "npx",

      "args": ["-y", "pqs-mcp-server"]

    }

  }

}

Remote (HTTP)

Use this when your MCP client supports streamable-HTTP transport (no local npm install required):

{

  "mcpServers": {

    "pqs": {

      "url": "https://promptqualityscore.com/api/mcp"

    }

  }

}

Smithery

smithery mcp add onchaintel/pqs

Tools

score_prompt (Free, no API key required)

Returns a 0-80 score, A-F grade, full 8-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. Rate-limited per IP: 5/min, 10/day, 100/month.

Low- and mid-band scores also include a structured suggestion field with a message, a next_tool pointer to optimize_prompt, and a subscribe URL the consuming LLM can paraphrase back to the user.

Example output (low-band score, suggestion attached):

{

  "pqs_version": "2.0",

  "prompt": "analyze this wallet",

  "score": 9,

  "out_of": 80,

  "grade": "F",

  "dimensions": {

    "clarity": 2,

    "specificity": 1,

    "context": 1,

    "constraints": 1,

    "output_format": 1,

    "role_definition": 1,

    "examples": 1,

    "cot_structure": 1

  },

  "weakest_dimension": "specificity",

  "powered_by": "PQS — promptqualityscore.com",

  "suggestion": {

    "message": "This prompt scored 9/80 (F) — significant room to improve. The optimize_prompt tool rewrites it and shows side-by-side outputs from a frontier model, so you can see the impact. optimize_prompt is part of PQS Pro ($19.99/mo, 1,000 calls/mo). Subscribe at https://promptqualityscore.com/pricing?utm_source=mcp&utm_medium=suggestion_v140&utm_campaign=2026-05-mcp-tools-v140.",

    "next_tool": "optimize_prompt",

    "subscribe_url": "https://promptqualityscore.com/pricing?utm_source=mcp&utm_medium=suggestion_v140&utm_campaign=2026-05-mcp-tools-v140"

  }

}

If the per-IP rate limit is hit, the response is a structured rate_limit_exceeded payload with subscribe and account URLs.

optimize_prompt (Pro subscription required)

Rewrites a prompt to score higher and runs both versions through a frontier model so the user can see the before/after output. Returns the optimized prompt, before/after dimension scores (with totals), improvement_pct, and side-by-side sample outputs.

Pro subscription required ($19.99/mo, 1,000 calls/mo, includes batch + A/B comparison). Subscribe at promptqualityscore.com/pricing.

If the API key is missing, invalid, or on the Free tier, the tool returns a structured error pointing the user at the right URL. No silent failures, no inventing keys. Errors emitted:

- api_key_required: no api_key argument was sent
- api_key_invalid: key not recognized
- subscription_required: key is valid but Free tier (subscribe to upgrade)
- rate_limited: per-minute burst limit reached (Pro is rate-limited per minute, not per month) or temporary upstream capacity issue
- service_unavailable: upstream 5xx

Quality Gate Pattern

Use PQS as a pre-inference quality gate:

const score = await fetch("https://promptqualityscore.com/api/score/free", {

  method: "POST",

  headers: { "Content-Type": "application/json" },

  body: JSON.stringify({ prompt: userPrompt })

});

const { score: pqsScore } = await score.json();

if (pqsScore < 56) throw new Error("Prompt quality too low. Improve and retry.");

Grade D or below (under 56/80) means the prompt will waste inference spend.

x402 (legacy pay-per-call)

The MCP tools in this package use the SaaS API-key model. A separate x402-native pay-per-call path is available via the canonical PQS HTTP API (no API key, caller settles USDC on Base on-chain). For x402 integration, see the canonical pricing and discovery artifacts at promptqualityscore.com.

Self-hosting

Override the PQS backend URL with the PQS_BASE environment variable:

PQS_BASE=https://your-pqs-host.example.com npx pqs-mcp-server

Defaults to https://promptqualityscore.com.

Built by

OnChainIntel, @OnChainAIIntel
promptqualityscore.com

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About

Details

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Setting up with Highlight

From the repository

score_prompt

optimize_prompt

Claude Desktop / Cursor

McpServers

PQS MCP Server

Install

Claude Desktop (stdio)

Remote (HTTP)

Smithery

Tools

score_prompt (Free, no API key required)

optimize_prompt (Pro subscription required)

Quality Gate Pattern

x402 (legacy pay-per-call)

Self-hosting

Built by

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